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Mining evidences for named entity disambiguation
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining, 2013Named entity disambiguation is the task of disambiguating named entity mentions in natural language text and link them to their corresponding entries in a knowledge base such as Wikipedia. Such disambiguation can help enhance readability and add semantics to plain text.
Yang Li 0150 +5 more
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Institution name disambiguation for research assessment
Scientometrics, 2013Research evaluation is a necessity for management of academic units (scientists, research groups, departments, institutes, universities) and for government decision making in science and technology. Yet, wrong conclusions may be drawn due to errors in assignments of authors to institutions.
Huang, Shuiqing +3 more
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Efficient Name Disambiguation in Digital Libraries
2011In digital libraries, ambiguous author names occur due to the existence of multiple authors with the same name or different name variations for the same person. Most of the previous works to solve this issue also known as name disambiguation often employ hierarchal clustering approaches based on information inside the citation records, e.g.
Jia Zhu 0003 +2 more
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Exploring personal name disambiguation from name understanding
2010 4th International Universal Communication Symposium, 2010The intensive studies have shown that the information in the context of the mentions of a person is very helpful for personal name disambiguation. However, it is not easy to exact all mentions of a person in text. In this paper, we investigate various mentions of a person in English and Chinese, and find that different languages often emphasize ...
Ying Chen 0012, Chu-Ren Huang
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Name Disambiguation Using Atomic Clusters
2008 The Ninth International Conference on Web-Age Information Management, 2008Name ambiguity is a critical problem in many applications, in particular in the online bibliography systems, such as DBLP and CiteSeer. Previously, several clustering based methods have been proposed although, the problem still presents to be a big challenge for both research and industry communities.
Feng Wang +4 more
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Serials Review, 2015
For the first installment of the new column, “Problem Solved!,” coedited by Kelly Smith and Scott Vieira, Vieira provides the first of two columns that will look into the nature of the problem surrounding author identity and how ORCID, a registry for author identifiers, may help resolve this challenge for researchers, publishers, and other institutions.
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For the first installment of the new column, “Problem Solved!,” coedited by Kelly Smith and Scott Vieira, Vieira provides the first of two columns that will look into the nature of the problem surrounding author identity and how ORCID, a registry for author identifiers, may help resolve this challenge for researchers, publishers, and other institutions.
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ELM-based name disambiguation in bibliography
World Wide Web, 2013It is common that different people share the same name. When it occurs in bibliography databases, it worsens the performance of information retrieval and data management. In this paper, we address the problem of name disambiguation and propose two different strategies, one classifier for each name (OCEN) and one classifier for all names (OCAN).
Donghong Han +4 more
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Online Person Name Disambiguation with Constraints
Proceedings of the 15th ACM/IEEE-CS Joint Conference on Digital Libraries, 2015While many clustering techniques have been successfully applied to the person name disambiguation problem, most do not address two main practical issues: allowing constraints to be added to the clustering process, and allowing the data to be added incrementally without clustering the entire database. Constraints can be particularly useful especially in
Madian Khabsa +2 more
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Bootstrapping active name disambiguation with crowdsourcing
Proceedings of the 22nd ACM international conference on Information & Knowledge Management, 2013Name disambiguation is a challenging and important problem in many domains, such as digital libraries, social media management and people search systems. Traditional methods, based on direct assignment using supervised machine learning techniques, seem to be the most effective, but their performances are highly dependent on the amount of training data,
Yu Cheng 0001 +4 more
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Named Entity Disambiguation Using HMMs
2013 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT), 2013In this paper we present a novel approach to disambiguate textual mentions of named entities against the Wikipedia knowledge base. The conditional dependencies between different named entities across Wikipedia are represented as a Markov network. In our approach, named entities are treated as hidden variables and textual mentions as observations.
Ayman Alhelbawy, Robert J. Gaizauskas
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